1. Modeling Crown Biomass for Three North Idaho Conifers Ann Abbott Rocky Mountain Research Station, Moscow Forestry Sciences Laboratory and University of Idaho

3. Objectives Develop allometric models to predict individual branch biomass and leaf area. Scale the branch level models up to the tree and predict whole tree branch biomass and leaf area. Use nonlinear mixed effects modeling to predict branch basal diameter from branch insertion height.

8. Sample from mixed species stands at Priest River Experimental Forest and UI School Forest Destructive sampling study using Douglas-Fir, Grand Fir and Western Hemlock in two North Idaho locations Focus on branch biomass and leaf area

10. Part 1: Allometric Equations predicting individual branch biomass from predictors Goal: Obtain allometric equations for branch biomass components and leaf area – Total biomass in branch (wood + needles) – Needle biomass – Branch wood biomass – Needle Area Generate initial equations at individual branch level, then scale up for tree level equations

17. Individual Branch Allometric Equations Branch Level: Full Models Wood biomass – R 2 = 0.89, 0.74, 0.89 Needle biomass – R 2 =0.65, 0.62, 0.82 Total branch biomass – R 2 = 0.93, 0.90, 0.95 Needle area – R 2 = 0.69, 0.62, 0.90 Branch Level: Reduced Models Wood biomass – R 2 = 0.86, 0.71., 0.86 Needle biomass – R 2 = 0.65, 0.54., 0.77 Total branch biomass – R 2 = 0.90, 0.84., 0.91 Needle area – R 2 = 0.69, 0.60, 0.89

19. Tree Level Allometric Equations Tree Level: Full Models Wood biomass – R 2 = 0.64, 0.67, 0.69 Needle biomass – R 2 = 0.68, 0.63, 0.60 Total branch biomass – R 2 = 0.93, 0.59, 0.56 Needle area – R 2 = 0.37, 0.40, 0.50 Tree Level: Reduced Models Wood biomass – R 2 = 0.64, 0.47, 0.56 Needle biomass – R 2 = 0.56, 0.39, 0.46 Total branch biomass – R 2 = 0.81, 0.46., 0.56 Needle area – R 2 = 0.37, 0.40, 0.50

20. Part 1 Conclusion Branch level equations provided good allometric fit for biomass components and needle area – Full models generally only needed branch length to improve fit Tree level (scaled) equations explain less variability in biomass components and needle area

21. Part 2: Predict Branch Basal Diameter from Insertion Height Goal: predict branch basal diameter from insertion height Feed predicted branch diameters into the allometric equations to predict branch biomass quantities from bole characteristics

23. Nonlinear asymptotic model Include autocorrelation function to account for lack of independence of branches Include variance model to account for increasing variance in branch diameter as they occur deeper into the crown

27. Part 2 Conclusion Nonlinear asymptotic model with autocorrelation and a power function variance model provides a good fit between branch basal diameter and insertion height on bole

28. Combining both models will allow branch biomass and leaf area predictions from branch insertion height on bole Next step is to add stem biomass model from the study trees for crown biomass prediction